Medical devices for mapping cardiac tissue

ABSTRACT

Medical devices and methods for making and using medical devices are disclosed. An example method may include a method of mapping the electrical activity of a heart. The method may include sensing a plurality of signals with a plurality of electrodes positioned within the heart, determining a dominant frequency of the plurality of signals and generating an alternate signal for each of the plurality of signals corresponding to the dominant frequency. The alternate signals may have a phase-shift corresponding to one of the plurality of signals. The method may also include displaying a characteristic of the alternate signal over time.

CROSS-REFERENCE TO RELATED APPLICATIONS

This application claims priority under 35 U.S.C. §119 to U.S.Provisional Application Ser. No. 61/991,235, filed May 9, 2014, theentirety of which is incorporated herein by reference.

TECHNICAL FIELD

The present disclosure pertains to medical devices, and methods formanufacturing medical devices. More particularly, the present disclosurepertains to medical devices and methods for mapping and/or ablatingcardiac tissue.

BACKGROUND

A wide variety of intracorporeal medical devices have been developed formedical use, for example, intravascular use. Some of these devicesinclude guidewires, catheters, and the like. These devices aremanufactured by any one of a variety of different manufacturing methodsand may be used according to any one of a variety of methods. Of theknown medical devices and methods, each has certain advantages anddisadvantages. There is an ongoing need to provide alternative medicaldevices as well as alternative methods for manufacturing and usingmedical devices.

BRIEF SUMMARY

This disclosure provides design, material, manufacturing method, and usealternatives for medical devices.

In a first example, a system for mapping the electrical activity of theheart is disclosed. The system includes a catheter shaft, a plurality ofelectrodes coupled to the catheter shaft and a processor coupled to thecatheter shaft. The processor is configured to collect a plurality ofsignals sensed by the plurality of electrodes, determine a dominantfrequency of the plurality of signals and generate an alternate signalfor each of the plurality of signals corresponding to the dominantfrequency. Further each of the alternate signals has a phase-shiftcorresponding to one of the plurality of signals. The processor may alsodisplay a characteristic of the alternate signal over time.

In addition or alternatively to the above, and in another exampledetermining a dominant frequency includes processing each of theplurality of signals using a Fourier Transform, generating a compositesignal based on the processed plurality of signals and identifying thefrequency with the maximum power in the composite signal.

In addition or alternatively to any one or more of the above, and inanother example the system includes band-pass filtering each of theprocessed plurality of signals.

In addition or alternatively to any one or more of the above, and inanother example band-pass filtering includes passing data in the 3 to 7Hz band for each of the processed plurality of signals.

In addition or alternatively to any one or more of the above, and inanother example generating a composite signal based on the processedplurality of signals includes generating a composite signal with a valueat each frequency that is one of a median value, a mean value, or a modevalue of the processed plurality of signals at each frequency.

In addition or alternatively to any one or more of the above, and inanother example the phase-shift of the alternate signal is based on thecomposite signal.

In addition or alternatively to any one or more of the above, and inanother example each alternate signal is a sinusoid.

In addition or alternatively to any one or more of the above, and inanother example each alternate signal is an analytic representation of asinusoid.

In addition or alternatively to any one or more of the above, and inanother example the analytic representation is generated by a Hilberttransform.

In addition or alternatively to any one or more of the above, and inanother example the analytic representation is a sawtooth.

In addition or alternatively to any one or more of the above, and inanother example the system includes determining a fiducial point on eachalternate signal. Further, the fiducial point on each alternate signalis one of the following: a point with a maximum negative derivative, apoint of zero-crossing, and a point at phase π/2.

In addition or alternatively to any one or more of the above, and inanother example the system includes determining an activation time foreach of the plurality of signals based on the identified fiducialpoints, generating an activation map based on the determined activationtimes for each of the plurality of signals, and displaying theactivation map.

In addition or alternatively to any one or more of the above, and inanother example displaying a characteristic of the alternate signal overtime includes displaying a dynamic map.

In addition or alternatively to any one or more of the above, and inanother example displaying a characteristic of the alternate signal overtime includes displaying one or more phase values of one or morealternate signals.

In addition or alternatively to any one or more of the above, and inanother example displaying a characteristic of the alternate signal overtime includes displaying the results of the Hilbert transform on adynamic map.

In addition or alternatively to any one or more of the above, and inanother example a method of mapping the electrical activity of a heartis disclosed. The method includes sensing a plurality of signals with aplurality of electrodes positioned within the heart, determining adominant frequency of the plurality of signals and generating analternate signal for each of the plurality of signals corresponding tothe dominant frequency. The alternate signals can have a phase-shiftcorresponding to one of the plurality of signals. The method can alsoinclude displaying a characteristic of the alternate signal over time.

In addition or alternatively to any one or more of the above, and inanother example determining a dominant frequency includes processingeach of the plurality of signals using a Fourier Transform, generating acomposite signal based on the processed plurality of signals, andidentifying the frequency with the maximum power in the compositesignal.

In addition or alternatively to any one or more of the above, and inanother example the method of mapping the electrical activity of a heartincludes band-pass filtering each of the processed plurality of signals.

In addition or alternatively to any one or more of the above, and inanother example band-pass filtering includes passing data in the 3 to 7Hz band for each of the processed plurality of signals.

In addition or alternatively to any one or more of the above, and inanother example generating a composite signal based on the processedplurality of signals includes generating a composite signal with a valueat each frequency that is one of a median value, a mean value, or a modevalue of the processed plurality of signals at each frequency.

In addition or alternatively to any one or more of the above, and inanother example the phase-shift of the alternate signal is based on thecomposite signal.

In addition or alternatively to any one or more of the above, and inanother example each alternate signal is a sinusoid.

In addition or alternatively to any one or more of the above, and inanother example each alternate signal is an analytic representation of asinusoid.

In addition or alternatively to any one or more of the above, and inanother example the analytic representation is generated by a Hilberttransform.

In addition or alternatively to any one or more of the above, and inanother example the analytic representation is a sawtooth.

In addition or alternatively to any one or more of the above, and inanother example the fiducial point on each alternate signal is one ofthe following: a point with a maximum negative derivative, a point ofzero-crossing, and a point at phase π/2.

In addition or alternatively to any one or more of the above, and inanother example the method includes determining an activation time foreach of the plurality of signals based on the identified fiducialpoints, generating an activation map based on the determined activationtimes for each of the plurality of signals, and displaying theactivation map.

In addition or alternatively to any one or more of the above, and inanother example a method for determining activation times in cardiacelectrical signals is disclosed. The method includes sensing a pluralityof cardiac electrical signals with a plurality of electrodes positionedwithin the heart and processing the plurality of signals. Processing theplurality of signals can include transforming the plurality of signalsinto the frequency domain. The method can also include generating acomposite signal from the processed plurality of signals, identifyingthe largest frequency component from the composite signal, determining aphase value for each of the plurality of signals at the identifiedfrequency and generating an approximation signal for each of theplurality of signals. The generated approximation signal can have aphase-shift. The method can also display a characteristic of theapproximation signal over time.

In addition or alternatively to any one or more of the above, and inanother example processing the plurality of signals includes removingdata outside of the 3 to 7 Hz band in each of the plurality of signals.

In addition or alternatively to any one or more of the above, and inanother example generating the composite signal from the processedplurality of signals includes determining the median value of all of theplurality of signals at each frequency, determining the mean value ofall of the plurality of signals at each frequency, or determining themode value of all of the plurality of signals at each frequency.

In addition or alternatively to any one or more of the above, and inanother example the method includes determining a fiducial point on eachapproximation signal, determining an activation time for each of theplurality of signals based on the identified fiducial points, generatingan activation map based on the determined activation times for each ofthe plurality of signals, and displaying the activation map.

In addition or alternatively to any one or more of the above, and inanother example a system for mapping the electrical activity of theheart is disclosed. The system includes a catheter shaft, a plurality ofelectrodes coupled to the catheter shaft and a processor coupled to thecatheter shaft. The processor can be configured to collect a pluralityof signals sensed by the plurality of electrodes, determine a dominantfrequency of the plurality of signals and generate an alternate signalfor each of the plurality of signals corresponding to the dominantfrequency. The alternate signals can have a phase-shift corresponding toone of the plurality of signals. The system can also include displayinga characteristic of the alternate signals over time.

In addition or alternatively to any one or more of the above, and inanother example to determine a dominant frequency of the plurality ofsignals, the processor is further configured to transform each of theplurality of signals into the frequency domain, generate a compositesignal from each of the transformed plurality of signals and determinethe frequency that has the maximum power in the composite signal.

In addition or alternatively to any one or more of the above, and inanother example each alternate signal is a sinusoid or a sawtooth.

In addition or alternatively to any one or more of the above, and inanother example each alternate signal is an analytic representation of asinusoid.

The above summary of some embodiments is not intended to describe eachdisclosed embodiment or every implementation of the present disclosure.The Figures, and Detailed Description, which follow, more particularlyexemplify these embodiments.

BRIEF DESCRIPTION OF THE DRAWINGS

The disclosure may be more completely understood in consideration of thefollowing detailed description in connection with the accompanyingdrawings, in which:

FIG. 1 is a schematic view of an example catheter system for accessing atargeted tissue region in the body for diagnostic and therapeuticpurposes;

FIG. 2 is a schematic view of an example mapping catheter having abasket functional element carrying structure for use in association withthe system of FIG. 1;

FIG. 3 is a schematic view of an example functional element including aplurality of mapping electrodes;

FIG. 4 is an illustration of an example electrogram signal in the timedomain and a corresponding frequency representation in the frequencydomain;

FIGS. 5A-5C are illustrations of example frequency spectrums and acorresponding composite frequency spectrum;

FIG. 6 is an illustration of an example composite frequency spectrum andits maximum power value;

FIGS. 7A-7B are illustrations of example electrograms overlaid by asinusoid signal;

FIGS. 8A-8B are illustrations of example phase-shifted alternativesignal sinusoids and corresponding dynamic displays;

FIG. 9 is an illustration of an example alternate sinusoid signaloverlaid an original signal;

FIG. 10 is an illustration of an example activation map displayingactivation times.

FIGS. 11A-11C are illustrations of example activation signals overlaidby probability distributions.

While the disclosure is amenable to various modifications andalternative forms, specifics thereof have been shown by way of examplein the drawings and will be described in detail. It should beunderstood, however, that the intention is not to limit the invention tothe particular embodiments described. On the contrary, the intention isto cover all modifications, equivalents, and alternatives falling withinthe spirit and scope of the disclosure.

DETAILED DESCRIPTION

For the following defined terms, these definitions shall be applied,unless a different definition is given in the claims or elsewhere inthis specification.

All numeric values are herein assumed to be modified by the term“about,” whether or not explicitly indicated. The term “about” generallyrefers to a range of numbers that one of skill in the art would considerequivalent to the recited value (e.g., having the same function orresult). In many instances, the terms “about” may include numbers thatare rounded to the nearest significant figure.

The recitation of numerical ranges by endpoints includes all numberswithin that range (e.g. 1 to 5 includes 1, 1.5, 2, 2.75, 3, 3.80, 4, and5).

As used in this specification and the appended claims, the singularforms “a”, “an”, and “the” include plural referents unless the contentclearly dictates otherwise. As used in this specification and theappended claims, the term “or” is generally employed in its senseincluding “and/or” unless the content clearly dictates otherwise.

It is noted that references in the specification to “an example”, “someexamples”, “other examples”, etc., indicate that the example describedmay include one or more particular features, structures, and/orcharacteristics. However, such recitations do not necessarily mean thatall examples include the particular features, structures, and/orcharacteristics. Additionally, when particular features, structures,and/or characteristics are described in connection with one example, itshould be understood that such features, structures, and/orcharacteristics may also be used connection with other examples whetheror not explicitly described unless clearly stated to the contrary. Also,when particular features, structures, and/or characteristics aredescribed in connection with one example, it is implicit that otherexamples may include less than all of the disclosed features,structures, and/or characteristics in all combinations.

The following detailed description should be read with reference to thedrawings in which similar elements in different drawings are numberedthe same. The drawings, which are not necessarily to scale, depictillustrative embodiments and are not intended to limit the scope of theinvention.

Mapping the electrophysiology of heart rhythm disorders often involvesthe introduction of a basket catheter (e.g. Constellation) or othermapping/sensing device having a plurality of sensors into a cardiacchamber. The sensors, for example electrodes, detect physiologicalsignals, such as cardiac electrical activity, at sensor locations. Itmay be desirable to have detected cardiac electrical activity processedinto electrogram signals that accurately represent cellular excitationthrough cardiac tissue relative to the sensor locations. A processingsystem may then analyze and output the signal to a display device.Further, the processing system may output the signal as processedoutput, such as a static or dynamic activation map. A user, such as aphysician, may use the processed output to perform a diagnosticprocedure.

FIG. 1 is a schematic view of a system 10 for accessing a targetedtissue region in the body for diagnostic and/or therapeutic purposes.FIG. 1 generally shows the system 10 deployed in the left atrium of theheart. Alternatively, system 10 can be deployed in other regions of theheart, such as the left ventricle, right atrium, or right ventricle.While the illustrated embodiment shows system 10 being used for ablatingmyocardial tissue, system 10 (and the methods described herein) mayalternatively be configured for use in other tissue ablationapplications, such as procedures for ablating tissue in the prostrate,brain, gall bladder, uterus, nerves, blood vessels and other regions ofthe body, including in systems that are not necessarily catheter-based.

System 10 includes a mapping catheter or probe 14 and an ablationcatheter or probe 16. Each probe 14/16 may be separately introduced intothe selected heart region 12 through a vein or artery (e.g., the femoralvein or artery) using a suitable percutaneous access technique.Alternatively, mapping probe 14 and ablation probe 16 can be assembledin an integrated structure for simultaneous introduction and deploymentin the heart region 12.

Mapping probe 14 may include flexible catheter body 18. The distal endof catheter body 18 carries three-dimensional multiple electrodestructure 20. In the illustrated embodiment, structure 20 takes the formof a basket defining an open interior space 22 (see FIG. 2), althoughother multiple electrode structures could be used. Structure 20 carriesa plurality of mapping electrodes 24 (not explicitly shown on FIG. 1,but shown on FIG. 2) each having an electrode location on structure 20and a conductive member. Each electrode 24 may be configured to sense ordetect intrinsic physiological activity, for example represented aselectrical signals, in an anatomical region adjacent to each electrode24.

In addition, electrodes 24 may be configured to detect activationsignals of the intrinsic physiological activity within the anatomicalstructure. For example, intrinsic cardiac electrical activity maycomprise repeating or semi-repeating waves of electrical activity withrelatively large spikes in activity at the beginning of activationevents. Electrodes 24 may sense such activation events and the times atwhich such activation events occur. Generally, electrodes 24 may senseactivation events at different times as an electrical activity wavepropagates through the heart. For instance, an electrical wave may beginnear a first group of electrodes 24, which may sense an activation eventat relatively the same time or within a relatively small window of time.As the electrical wave propagates through the heart, a second group ofelectrodes 24 may sense the activation event of the electrical wave attimes later than the first group of electrodes 24.

Electrodes 24 are electrically coupled to processing system 32. A signalwire (not shown) may be electrically coupled to each electrode 24 onstructure 20. The signal wires may extend through body 18 of probe 14and electrically couple each electrode 24 to an input of processingsystem 32. Electrodes 24 sense cardiac electrical activity in theanatomical region, e.g., myocardial tissue, adjacent to their physicallocation within the heart. The sensed cardiac electrical activity (e.g.,electrical signals generated by the heart which may include activationsignals) may be processed by processing system 32 to assist a user, forexample a physician, by generating processed output—e.g. an anatomicalmap (e.g., a vector field map, an activation time map) or a Hilberttransform diagram—to identify one or more sites within the heartappropriate for a diagnostic and/or treatment procedure, such as anablation procedure. For example, processing system 32 may identify anear-field signal component (e.g., activation signals originating fromcellular tissue adjacent to mapping electrodes 24) or an obstructivefar-field signal component (e.g., activation signals originating fromnon-adjacent tissue). In such examples where structure 20 is disposed inan atrium of the heart, as in FIG. 1, the near-field signal componentmay include activation signals originating from atrial myocardial tissuewhereas the far-field signal component may include activation signalsoriginating from ventricular myocardial tissue. The near-fieldactivation signal component may be further analyzed to find the presenceof a pathology and to determine a location suitable for ablation fortreatment of the pathology (e.g., ablation therapy).

Processing system 32 may include dedicated circuitry (e.g., discretelogic elements and one or more microcontrollers; application-specificintegrated circuits (ASICs); or specially configured programmabledevices, such as, for example, programmable logic devices (PLDs) orfield programmable gate arrays (FPGAs)) for receiving and/or processingthe acquired physiological activity. In some examples, processing system32 includes a general purpose microprocessor and/or a specializedmicroprocessor (e.g., a digital signal processor, or DSP, which may beoptimized for processing activation signals) that executes instructionsto receive, analyze and display information associated with the receivedphysiological activity. In such examples, processing system 32 caninclude program instructions, which when executed, perform part of thesignal processing. Program instructions can include, for example,firmware, microcode or application code that is executed bymicroprocessors or microcontrollers. The above-mentioned implementationsare merely exemplary, and the reader will appreciate that processingsystem 32 can take any suitable form for receiving electrical signalsand processing the received electrical signals.

In addition, processing system 32 may be configured to measure thesensed cardiac electrical activity in the myocardial tissue adjacent toelectrodes 24. For example, processing system 32 may be configured todetect cardiac electrical activity associated with a dominant rotor ordivergent activation pattern in the anatomical feature being mapped.Dominant rotors and/or divergent activation patterns may have a role inthe initiation and maintenance of atrial fibrillation, and ablation ofthe rotor path, rotor core, and/or divergent foci may be effective interminating the atrial fibrillation. Processing system 32 processes thesensed cardiac electrical activity to generate a display of relevantcharacteristics. Such processed output may include isochronal maps,activation time maps, action potential duration (APD) maps, Hilberttransform diagrams, vector field maps, contour maps, reliability maps,electrograms, cardiac action potentials and the like. The relevantcharacteristics may assist a user to identify a site suitable forablation therapy.

Ablation probe 16 includes flexible catheter body 34 that carries one ormore ablation electrodes 36. The one or more ablation electrodes 36 areelectrically connected to radio frequency (RF) generator 37 that isconfigured to deliver ablation energy to the one or more ablationelectrodes 36. Ablation probe 16 may be movable with respect to theanatomical feature to be treated, as well as structure 20. Ablationprobe 16 may be positionable between or adjacent to electrodes 24 ofstructure 20 as the one or more ablation electrodes 36 are positionedwith respect to the tissue to be treated.

Processing system 32 may output data to a suitable device, for exampledisplay device 40, which may display relevant information for a user. Insome examples, device 40 is a CRT, LED, or other type of display, or aprinter. Device 40 presents the relevant characteristics in a formatuseful to the user. In addition, processing system 32 may generateposition-identifying output for display on device 40 that aids the userin guiding ablation electrode(s) 36 into contact with tissue at the siteidentified for ablation.

FIG. 2 illustrates mapping catheter 14 and shows electrodes 24 at thedistal end suitable for use in system 10 shown in FIG. 1. Mappingcatheter 14 may include flexible catheter body 18, the distal end ofwhich may carry three-dimensional multiple electrode structure 20 withmapping electrodes or sensors 24. Mapping electrodes 24 may sensecardiac electrical activity, including activation signals, in themyocardial tissue. The sensed cardiac electrical activity may beprocessed by the processing system 32 to assist a user in identifyingthe site or sites having a heart rhythm disorder or other myocardialpathology via generated and displayed relevant characteristics. Thisinformation can then be used to determine an appropriate location forapplying appropriate therapy, such as ablation, to the identified sites,and to navigate the one or more ablation electrodes 36 to the identifiedsites.

The illustrated three-dimensional multiple electrode structure 20comprises base member 41 and end cap 42 between which flexible splines44 generally extend in a circumferentially spaced relationship. Asdiscussed herein, structure 20 may take the form of a basket defining anopen interior space 22. In some examples, the splines 44 are made of aresilient inert material, such as Nitinol, other metals, siliconerubber, suitable polymers, or the like and are connected between basemember 41 and end cap 42 in a resilient, pretensioned condition, to bendand conform to the tissue surface they contact. In the exampleillustrated in FIG. 2, eight splines 44 form three dimensional multipleelectrode structure 20. Additional or fewer splines 44 could be used inother examples. As illustrated, each spline 44 carries eight mappingelectrodes 24. Additional or fewer mapping electrodes 24 could bedisposed on each spline 44 in other examples of three dimensionalmultiple electrode structure 20. In the example illustrated in FIG. 2,structure 20 is relatively small (e.g., 40 mm or less in diameter). Inalternative examples, structure 20 is even smaller or larger (e.g., lessthan or greater than 40 mm in diameter).

Slidable sheath 50 may be movable along the major axis of catheter body18. Moving sheath 50 distally relative to catheter body 18 may causesheath 50 to move over structure 20, thereby collapsing structure 20into a compact, low profile condition suitable for introduction intoand/or removal from an interior space of an anatomical structure, suchas, for example, the heart. In contrast, moving sheath 50 proximallyrelative to the catheter body may expose structure 20, allowingstructure 20 to elastically expand and assume the pretensioned positionillustrated in FIG. 2.

A signal wire (not shown) may be electrically coupled to each mappingelectrode 24. The signal wires may extend through body 18 of mappingcatheter 20 (or otherwise through and/or along body 18) into handle 54,in which they are coupled to external connector 56, which may be amultiple pin connector. Connector 56 electrically couples mappingelectrodes 24 to processing system 32. It should be understood thatthese descriptions are just examples. Some addition details regardingthese and other example mapping systems and methods for processingsignals generated by a mapping catheter can be found in U.S. Pat. Nos.6,070,094, 6,233,491, and 6,735,465, the disclosures of which are herebyexpressly incorporated herein by reference.

To illustrate the operation of system 10, FIG. 3 is a schematic sideview of an example of basket structure 20 including a plurality ofmapping electrodes 24. In the illustrated example, the basket structureincludes 64 mapping electrodes 24. Mapping electrodes 24 are disposed ingroups of eight electrodes (labeled 1, 2, 3, 4, 5, 6, 7, and 8) on eachof eight splines (labeled A, B, C, D, E, F, G, and H). While anarrangement of sixty-four mapping electrodes 24 is shown disposed onbasket structure 20, mapping electrodes 24 may alternatively be arrangedin different numbers (more or fewer splines and/or electrodes), ondifferent structures, and/or in different positions. In addition,multiple basket structures can be deployed in the same or differentanatomical structures to simultaneously obtain signals from differentanatomical structures.

After basket structure 20 is positioned adjacent to the anatomicalstructure to be treated (e.g. left atrium, left ventricle, right atrium,or right ventricle of the heart), processing system 32 is configured torecord the cardiac electrical activity from each electrode 24 channel,and the cardiac electrical activity is related to physiological activityof the adjacent anatomical structure. For instance, cardiac electricalactivity may include activation signals which may indicate an onset ofphysiological activity, such as a contraction of the heart. Electrodes24 sense such cardiac electrical activity which includes activationsignals. The cardiac electrical activity of physiological activity maybe sensed in response to intrinsic physiological activity (e.g.intrinsically generated electrical signals) or based on a predeterminedpacing protocol instituted by at least one of the plurality ofelectrodes 24 (e.g. delivered electrical signals delivered by a pacingdevice).

The arrangement, size, spacing and location of electrodes along aconstellation catheter or other mapping/sensing device, in combinationwith the specific geometry of the targeted anatomical structure, maycontribute to the ability (or inability) of electrodes 24 to sense,measure, collect and transmit electrical activity of cellular tissue. Asstated, because splines 44 of a mapping catheter, constellation catheteror other similar sensing device are bendable, they may conform to aspecific anatomical region in a variety of shapes and/or configurations.Further, at any given position in the anatomical region, structure 20may be manipulated such that one or more splines 44 may not contactadjacent cellular tissue. For example, splines 44 may twist, bend, orlie atop one another, thereby separating splines 44 from nearby cellulartissue. Additionally, because electrodes 24 are disposed on one or moreof splines 44, they also may not maintain contact with adjacent cellulartissue. Electrodes 24 that do not maintain contact with cellular tissuemay be incapable of sensing, detecting, measuring, collecting and/ortransmitting electrical activity information. Further, becauseelectrodes 24 may be incapable of sensing, detecting, measuring,collecting and/or transmitting electrical activity information,processing system 32 may be incapable of accurately displayingdiagnostic information and/or processed output. For example, somenecessary information may be missing and/or displayed inaccurately.

In addition to that stated above, electrodes 24 may not be in contactwith adjacent cellular tissue for other reasons. For example,manipulation of mapping catheter 14 may result in movement of electrodes24, thereby creating poor electrode-to-tissue contact. Further,electrodes 24 may be positioned adjacent fibrous, dead or functionallyrefractory tissue. Electrodes 24 positioned adjacent fibrous, dead orfunctionally refractory tissue may not be able to sense changes inelectrical potential because fibrous, dead or functionally refractorytissue may be incapable of depolarizing and/or responding to changes inelectrical potential. Finally, far-field ventricular events andelectrical line noise may distort measurement of tissue activity.

However, electrodes 24 that contact healthy, responsive cellular tissuemay sense a change in the voltage potential of a propagating cellularactivation wavefront. The change in voltage potential of cellular tissuemay be sensed, collected and displayed as an electrogram. An electrogrammay be a visual representation of the change in voltage potential of thecellular tissue over time. Additionally, it may be desirable to define aspecific characteristic of an electrogram as a “fiducial” point of theelectrical signal. For purposes of this disclosure, a fiducial point maybe understood as a characteristic of an electrogram that can be utilizedas an identifying characteristic of cellular activation. Fiducial pointsmay correspond to the peak amplitude, change in slope, and/or deflectionof the electrical signal. It is contemplated that fiducial points mayinclude other characteristics of an electrogram or other signal used togenerate diagnostic and/or processed output. Further, fiducial pointsmay be identified manually by a clinician and/or automatically byprocessing system 32.

An electrogram representing a change in voltage potential over time maybe defined as visually displaying the electrical signal in the “timedomain.” However, it is generally understood that any electrical signalhas a corollary representation in the “frequency domain.” Transforms(e.g. Fourier, Fast Fourier, Wavelet, Wigner-Ville) may be utilized totransform signals between the time (spatial) domain and frequencydomain, as desired. Electrical signals also have a corollaryrepresentation in the analytic domain which can be obtained throughtransforms (e.g. Hilbert transform).

Further, in a normal functioning heart, electrical discharge of themyocardial cells may occur in a systematic, linear fashion. Therefore,detection of non-linear propagation of the cellular excitation wavefrontmay be indicative of cellular firing in an abnormal fashion. Forexample, cellular firing in a rotating pattern may indicate the presenceof dominant rotors and/or divergent activation patterns. Further,because the presence of the abnormal cellular firing may occur overlocalized target tissue regions, it is possible that electrical activitymay change form, strength or direction when propagating around, within,among or adjacent to diseased or abnormal cellular tissue.Identification of these localized areas of diseased or abnormal tissuemay provide a user with a location for which to perform a therapeuticand/or diagnostic procedure. For example, identification of an areaincluding reentrant or rotor currents may be indicative of an area ofdiseased or abnormal cellular tissue. The diseased or abnormal cellulartissue may be targeted for an ablative procedure. Various processedoutputs, such as those described above, may be used to identify areas ofcircular, adherent, rotor or other abnormal cellular excitationwavefront propagation.

In at least some embodiments, the process of generating processed outputmay begin by collecting signals from one or more of sixty-fourelectrodes 24 on structure 20. As stated above, the sensed signals maybe collected and displayed in the time domain. However, in at least oneembodiment, signals displayed in the time domain may be transformed intothe frequency domain to further generate processed output. As statedabove, transforms such as the Fourier Transform, Fast Fourier Transform,or any other transform that produces frequency and power information fora signal may be utilized to transform signals between the time andfrequency domains. FIG. 4 illustrates an example electrogram signal inthe time domain 60 along with its corresponding frequency representationin the frequency domain 62.

After transforming the signal into the frequency domain, processingsystem 32 may construct, determine or calculate a composite signal orcharacteristic (e.g. frequency) common to one or more of the signalscollected from the sixty-four electrodes 24 on structure 20. Thecomposite signal may be constructed, determined or calculated byperforming one or more mathematical, statistical or computationaloperations involving one or more of the signals collected from thesixty-four electrodes 24 on structure 20. For example, the compositesignal may be determined by calculating the median amplitude and/orpower value at each frequency for one or more of the signals collectedfrom the sixty-four electrodes 24 on structure 20. FIG. 5c illustrates acomposite signal 66 derived from contributing signals 68 and 70, shownin FIGS. 5a and 5b , respectively. FIG. 5c may illustrate a compositesignal created by calculating the median power value for each frequencyacross signals 68 and 70. It should be understood that processing system32 may incorporate sensed data values from one or more of the collectedsignals from one or more of the sixty-four electrodes 24 on structure20. Further, calculating the statistical median for all frequenciesacross one or more signals is one of numerous possible methodologiesprocessing system 32 may utilize to construct, determine or calculate acomposite signal. For example, processing system 32 may utilize themean, median, mode or any other mathematical, statistical orcomputational operation to construct, determine or calculate a compositesignal.

Additionally, processing system 32 may determine a “characteristicfrequency” from a generated composite signal. For example, aftercalculating the median power value for each frequency across collectedsignals, processing system 32 may determine the frequency at which themaximum power value occurs. The frequency at which the maximum powervalue occurs may represent the “median dominant frequency” of one ormore collected signals contributing to the composite signal. This mediandominant frequency may be considered the “characteristic frequency” ofthe collected signals. FIG. 6, for example, illustrates an examplecomposite signal 72 and the frequency corresponding to its maximum powervalue 74.

As stated above, processing system 32 may utilize the mean, median, modeor any other mathematical, statistical or computational operation toconstruct, determine or calculate a composite signal. Additionally, thecharacteristic frequency may represent the median dominant, meandominant frequency, mode dominant frequency or any other dominant orcharacteristic frequency derived from a variety of computationaloperations. Further, it should be understood that processing system 32may not have to calculate a composite signal in order to generate,determine, select or derive a characteristic frequency. Rather, it maybe possible for processing system 32 to determine a unique compositecharacteristic by analyzing the data collected from one or more of thesignals collected from the sixty-four electrodes 24 on structure 20independently of determining a composite signal.

Additionally, processing system 32 may select a range of frequencies forwhich data is utilized from one or more of the signals collected fromthe sixty-four electrodes 24 on structure 20. For example, a frequencyrange of 3-7 Hz has been shown (empirically) to be a frequency range inwhich abnormal cardiac electrical activity occurs. For example, atrialfibrillation may occur predominantly in the frequency range of 3-7 Hz.It is contemplated that other abnormal atrial events may also occurwithin this frequency range.

To that end, it may be desirable to filter and exclude collectedelectrical signal data outside of the 3-7 Hz frequency range. This maybe accomplished by utilizing a bandpass filter having a passing regionbetween 3-7 Hz. In other embodiments, processing system 32 may determinea composite signal or characteristic frequency by determining a median,mean, mode or other signal characteristic for frequencies between 3-7 Hzfor each collected signal, thereby eliminating the need for a filteringstep. Additionally, it should be understood that the selected and/orfiltered frequency range may be greater or less than 3-7 Hz (e.g. eachlimit could be modified by ±2-10 Hz). Selecting or ignoring data withina particular frequency range may improve the techniques and/or processedoutput of the embodiments disclosed herein.

Additionally, processing system 32 may determine a phase valueassociated with a characteristic of the collected electrical signals.For example, processing system 32 may determine a phase value correlatedto a determined characteristic frequency for one or more of the signalscollected from electrodes 24 on structure 20. Further, a phase value maybe determined at the median dominant frequency for one or more of thesignals collected from electrodes 24 on structure 20. Additionally, theFourier transform may be used to determine the phase value for aparticular collected signal at a given frequency. Therefore, the Fouriertransform may be used to determine the phase value for one or more ofthe signals collected from electrodes 24 on structure 20 at acharacteristic frequency (e.g. the median dominant frequency).

In addition, processing system 32 may generate an alternate signalassociated and/or correlated to each of the signals collected fromelectrodes 24 on structure 20. An alternate signal corresponding to eachcollected signal may include related and important features of thecollected signal

In the examples that follow, alternate signals may be described assinusoids. However, it is contemplated that any of examples and/orembodiments that describe an alternate signal as a sinusoid may also bedescribed by its analytic representation. For example, the analyticrepresentation of a signal may be understood as a complex representationof the signal with no negative frequency components. The phase of thesignal at each time point can be readily obtained from this analyticrepresentation by comparing its real component with this imaginarycomponent at each time point. The analytic signal may take the shape ofa “sawtooth” wave pattern. The analytic signal representation may beobtained through the Hilbert transform. Further, it is contemplated thatan alternate signal may be a signal other than a sinusoid and/or itsanalytic representation.

Additionally, it should be understood that an alternate signalcorrelated to a signal collected from electrodes 24 may containcharacteristics related to the composite signal, compositecharacteristic and/or a dominant frequency of one or more of thecollected signals. For example, the alternate signal may have a dominantfrequency that is equal to the dominant frequency of the compositesignal, composite characteristic and/or a dominant frequency of one ormore of the collected signals from electrodes 24. In embodiments wherethe alternate signal is a sinusoid, the sinusoid may have a frequencyequal to the dominant frequency of the composite signal, compositecharacteristic and/or a dominant frequency of one or more of thecollected signals from electrodes 24. Further, alternate signals maycontain additional information, such as amplitude, that reflect voltagevalues of one or more signals collected by electrodes 24. In addition,an alternate signal may display a consistent or repeated pattern thataligns with a collected signal (that may not display a uniform orconsistent pattern over time). For example, an alternate sinusoid signal(displaying a uniform oscillation over a time period) may be correlatedto an original (e.g. unipolar) signal whose amplitude and frequencyvaries significantly over the same time period. It should be understoodthat a time period described in the examples above may include and/orspan N beats of an arrhythmic cardiac event (e.g. atrial fibrillation).

Additionally, to better utilize information derived from alternatesignals, it may be desirable to align one or more alternate signals withone or more corresponding original, collected signals. The phase valuederived from the frequency spectrum of a collected signal may beutilized to adjust, shift and/or correlate an alternate signal to itsoriginal (e.g. unipolar) signal. For example, alternate signals that aresinusoids may be assigned a phase value derived from their correspondingcollected (e.g. unipolar) signal. The phase value may be used to modifyor better align the alternate signal with the collected signal.Adjustment and/or modification of an alternate signal using the phasevalue may provide a more accurate estimation of important diagnosticinformation associated with the collected signals. For example, FIG. 7aillustrates original signal 78 overlaid by its unshifted alternatesinusoid signal 76. In FIG. 7a , the maximum negative derivative 82 oforiginal signal 78 does not align with downstroke 80 of sinusoid 76.However, as shown in FIG. 7b , shifting sinusoid 76 by a phase value maybetter align the downstroke 80 of sinusoid 76 with the maximum negativederivative of collected signal 78.

Additionally, after one or more alternate signals have beenphase-shifted to better align with the collected signals, it may bedesirable to compare the amplitudes of one or more of the alternate(e.g., sinusoid, Hilbert representation, etc.) signals over time. Forexample, as stated above, depending on the characteristics of itscorresponding original signal, the amplitude value of a given alternatesignal may differ as compared to a second alternate signal derived froma second original signal. Further, the amplitude values (at a giventime) may differ for one or more of the alternate signals derived fromone or more of the signals collected from electrodes 24. For example,FIG. 8b shows an example “amplitude vs. time” plot of phase-shifted,alternate sinusoid signals 71, 73, 75 and 77. FIG. 8b illustrates thatat time point 79, phase-shifted, alternate sinusoid signals 71, 73, 75and 77 may have different amplitude values 81, 83, 85 and 87,respectively. Further, it is understood that the amplitude value of anyone of signals 71, 73, 75 and 77 will change over a given time period.

To that end, it may be desirable to compare the amplitude values of oneor more alternate signals over a given time period. Further, it may bedesirable to display the numerical values of the amplitudes in a dynamicdisplay. For example, it may be desirable to generate a “movie” or“dynamic display” comparing the amplitudes sensed by electrodes 24. FIG.8a shows example dynamic display 67 displaying amplitude values (e.g.,corresponding to amplitude values 81, 83, 85 and 87 of signals 71, 73,75 and 77) in spaces 89, 91, 93 and 95. It can be appreciated thatdifferent numeric amplitude values may be represented by a colorspectrum. For example, a given color (e.g. red) may represent amplitudevalues of 0-0.1, while a different color (e.g. orange) may representamplitude values of 0.11-0.2, for example. FIG. 8a shows spaces 89, 91,93 and 95 which correspond to amplitude values 81, 83, 85 and 87 ofsignals 71, 73, 75 and 77. Further, spaces 89, 91, 93 and 95 displaydifferent cross-hatch patterns as compared to one another. The differentcross-hatch patterns may represent different colors as they relate tothe specific amplitude values 81, 83, 85 and 87 of signals 71, 73, 75and 77.

It is understood that over a given time period, the colors of spaces 89,91, 93 and 95 will change as the amplitude values 81, 83, 85 and 87 ofsignals 71, 73, 75 and 77 change. Further, it should be understood thatalternate signals 81, 83, 85 and 87 may correspond to four of sixty-fourelectrodes 24 on structure 20. It should be further understood thatFIGS. 8a and 8b are only illustrative, and therefore, may represent anynumber of the sixty-four electrodes 24 on structure 20. Over time, thecontinual changing of colors may be displayed, or “played” as a dynamicdisplay or movie representing the sixty-four electrodes 24 on structure20. This movie or dynamic display may provide a medium that allowsbetter visualization of the cellular wavefront propagation and/or thefocal impulse of cellular activity over N beats of an arrhythmic cardiacevent (e.g. atrial fibrillation).

Utilizing the amplitude values derived from alternate sinusoid signals(or analytic representation) may provide a “smoothing effect” to thedynamic display as compared to utilizing amplitude values deriveddirectly from original, collected signals. Further, application of theHilbert transform to the alternate sinusoid signals may result in adynamic display that is clearer than displays generated by otheralternative signals.

In addition to generating a dynamic display, it may be desirable togenerate a static display from fiducial points (e.g. activation times)derived from alternate signals. A fiducial point may be understood as acharacteristic of an electrogram that can be utilized to identifycellular activation (e.g. cellular depolarization). For example, it iscontemplated that fiducial points may include any characteristic of asinusoid signal during its phase length. For example, activation timesmay be correlated to peak amplitude, phase, maximum negative derivativeor zero-crossing. These are just examples.

Further, it may be desirable to display an activation map related tofiducial points derived from alternative sinusoid signals. Theactivation map may represent the relative activation times of electrodes24 for one cycle in a multi-cycle cardiac event. In contrast to thedynamic display, an activation map may need to be “refreshed” for eachcycle in a multi-cycle cardiac event.

For the purposes of this disclosure, the time at which a fiducial pointoccurs relative to a reference time (the reference time may be the timea reference electrode senses a cellular activation and, for convenience,is set to 0) corresponds to the activation time for a given electrode.The various times that are determined as the activation times for eachof the alternate signals may be compared, categorized and/or displayed.The activation times may be displayed in an activation map 99 asillustrated in FIG. 10.

Alternatively, it may be desirable to determine the “true” activationtimes of the original, collected signals. However, selecting activationtimes from the original signal characteristics may prove challenging.For example, automated activation time selection on original (e.g.unipolar) signals may result in the mislabeling of fiducial points,thereby leading to faulty interpolation of multi-electrode array data.Further, increased processing power may be required to implementmethodologies and algorithms associated with automated selection.Therefore, it may be desirable to utilize a methodology which moreefficiently and/or accurately determines the “true” activation times oforiginal, sensed signals.

In some embodiments, sensing the “true” activation time may beaccomplished by aligning an “estimated” fiducial point on an alternatesignal with that of the “true” activation time of the original signal.For example, it may desirable to determine true activation times bycomparing and/or relating signal characteristics of the original andalternate signals. For example, processing system 32 may determine thetime at which the zero-crossing on the alternate signal occurs. Havingdetermined the time at which zero-crossing on the alternate signaloccurs, processing system 32 may compare that time with the time atwhich the maximum negative derivative on the original signal occurs. Ifthe time at which the original signal characteristic occurs issufficiently close to the time at which the alternate signalcharacteristic occurs, processing system 32 may assign the time at whichthe original signal characteristic (e.g. maximum negative derivative)occurs as the activation time of the original signal. In other words, inorder to provide increased confidence that a given signal characteristic(e.g. maximum negative derivative) accurately represents the trueactivation time of cellular tissue, processing system may create a“window” or “tolerance window” of time around the time at which thealternate signal characteristic occurs and determine whether a givensignal characteristic on the original signal falls within that “window”of time.

FIG. 9 illustrates an example schematic of the “windowing” methodologydescribed above. FIG. 9 displays electrogram 84 overlaid with a plot ofits negative derivative 86 and alternate sinusoid signal 88. Asillustrated in FIG. 9, electrogram 84 has a maximum negative derivativevalue 92 that correlates with the maximum negative slope 94 ofelectrogram 84 at time point 96. While not illustrated in FIG. 9,processing system 32 may detect other time values at which electrogram84 displays a downward slope and corresponding negative derivative. Insome embodiments, processing system may select the time point of themaximum negative derivative of the electrogram as the activation time ofthe sensed electrogram signal.

Additionally, processing system 32 may select the time point of themaximum negative derivative of the electrogram as the activation time ofthe electrogram signal 84 only if the time point lies within apredetermined “window” of time as compared to a zero-crossing point ofan alternate signal. For example, FIG. 9 illustrates zero-crossing point90 of alternate sinusoid signal 88 occurring at example time point 98.Processing system 32 may compare time point 96 (corresponding to themaximum negative derivative value 92) with time point 98 (correspondingto the zero-crossing point of alternate signal 88). If time point 96 iswithin the predetermined “window” of time, processing system 32 mayselect time point 96 as the activation time of electrogram signal 84. Itis contemplated that the “window” of time value may be user determinedand/or pre-programmed into a selection algorithm of processing system32, such as “% of cycle length” or a “multiplier of cycle length.”

Additionally, it is contemplated that processing system 32 may, overtime, adjust the frequency and phase of the alternate signal bycomparing the selected activation times on the original (e.g.electrogram) signal with the corresponding zero-crossing points (orother fiducial point) on the alternate signal. For example, processingsystem may compare the original signal and alternate signal time pointsover the near-term historical data (e.g. last N beats of a cardiaccycle). Further, a constant offset or difference between the selectedactivation times and corresponding zero-crossing on the alternate signalover the last N beats indicates that the phase of the alternate signalis off and may be adjusted to mitigate the constant offset.Additionally, an offset or difference that systematically increases (ordecreases) over the last N beats, for example, may indicate that thefrequency of the alternate signal is higher (or lower) than optimal andmay be adjusted to mitigate the slope of the difference over the last Nbeats. A regression may be performed over the difference between theselected activation times and corresponding zero-crossing on thealternate signal over the last N beats as a function of beat number.Further, the resultant slope and intercept could be used toupdate/adjust the frequency and phase of the alternate signal. Theprocess can be repeated periodically.

In addition, processing system 32 may utilize “threshold” values forwhich signal characteristics must meet in order for processing system 32to include them in an algorithm, process or calculation of processedoutput (e.g. activation times). For example, processing system 32 mayuse a “maximum derivative magnitude” as a threshold value for themaximum negative derivative calculation. Additionally, if processingsystem 32 fails to identify signal characteristics that meetpredetermined threshold values, processing system 32 may use fiducialtime points as the default assignment of processed output (e.g.activation times). For example, if the a signal characteristic on anoriginal signal (e.g. maximum negative derivative) does not fall withina chosen “window of time” as described above or does not meet a maximumderivative threshold, the signal characteristic on the alternate signal(e.g. zero-crossing) may be selected as the processed output (e.g.activation time).

While the above examples identify the original and the alternate signalcharacteristics as the maximum negative derivative and thezero-crossing, respectively, it should be understood that signalcharacteristics may be any characteristic other than, or in addition, tothose identified above.

While the “windowing” methodology described above may be useful inselecting and/or determining true activation times, other methods arecontemplated. For example, processing system 32 may incorporate astatistical-based methodology and/or algorithm to predict, refine andselect true activation times from original, sensed signals. In oneexample methodology, processing system 32 may incorporate known orsensed data (e.g., activation times and/or electrograms) to generate theprobability of the occurrence of future activation times. As data iscollected, processing system 32 may adjust the statistical algorithmbased on previously collected data. Selection of true activation pointsof future activation wavefronts may then be based on a probabilitydistribution calculated by the past activation events. Furthermore, thestatistical-based algorithm may attempt to introduce and/or modelsources of uncertainty within the statistical model. In someembodiments, utilizing a statistical algorithm may require processingsystem 32 to first generate an “activation” signal for each of theoriginal signals from one or more of electrodes 24 on structure 20 and,second, use the activation signals to estimate an overall cycle lengthof the arrhythmic cardiac event.

Generating an activation signal for each electrode location on a sensingdevice may include sensing and converting the original signals tomodified signal. An activation signal for each electrode location mayincorporate the data sensed by the individual electrode location over aperiod of time. For example, an activation signal may include datasensed over N beats of an arrhythmic cardiac event (e.g. atrialfibrillation). Further, modifying the original signals may includeselecting important signal information while eliminating and/orfiltering less-desirable information. For example, original, sensedsignals may include three primary components: far-field activation,local activation and power line noise. In contrast, activation signalsmay eliminate a portion or all of these three primary components.

To that end, power line noise may be reduced and/or removed by utilizingan adaptive filter. Additionally, a spatial filter may be utilized toremove far-field signals. Far field signals may be present in electrodes24 which are not in contact with cardiac tissue. Therefore, a spatialfilter may use a first-order polynomial model based on the approximateshape of the sensing device (e.g. Constellation catheter).Alternatively, many of the same benefits to using an adaptive filter toremove power line noise and a spatial filter to remove far-field signalsmay be achieved by subtracting the mean (or a weighted mean) of themeasured signals.

The next steps in generating activation signals may include: calculatingthe first-difference of each measurement, setting the positive values tozero (thereby discarding positive deflections), applying a low-passfilter to smooth out multiple deflections and inverting the activationsignal such that it is positive-valued.

As stated above, after generating an activation signal for eachelectrode location, the next step in a statistical-based methodology isutilizing the activation signals to estimate the overall cycle length ofthe arrhythmic cardiac event. For example, the steps may includecomputing the power spectrum (e.g. by utilizing Welch's method) of eachactivation signal, adding a noise floor, taking the FFT of the log powerspectrum to get the cepstrum, averaging the cepstra of the electrodes,and selectively choosing peak values to derive the cycle length.

After determining both the activation signal and estimating the cyclelength, the next step in utilizing a statistical-based methodology toselect activation times for each electrode may include utilizing an“iterative” statistical algorithm. For example, the methodology mayinclude using Bayes method to iteratively refine future activation timedata based on probability distributions of past activation times.

FIGS. 11a-11c illustrate an example statistical algorithm using theactivation signal and cycle length (described above) along with Bayesmethod to determine true activation times of example cardiac wavefronts.FIGS. 11a, 11b and 11c represent the steps performed by the statisticalalgorithm spanning three beats of a cardiac cycle. The first step in thestatistical algorithm may include utilizing a pre-selected,initialization probability function as a first predication of theprobability of cellular activation times. In FIG. 11a , initializationprobability function 49 is illustrated under the column titled “Beat 1.”The next step in the statistical algorithm may include smoothinginitialization probability function 49 with a low pass filter. This stepmay result in a Gaussian-shaped smoothed probability function 51, whichis illustrated under the column titled “Beat 1” of FIG. 11b . It shouldbe understood that this “smoothing” step may not be necessary for thefirst initialization step. However, the “smoothing” step models theuncertainty in predicting subsequent activation times. In someembodiments the smoothed probability function 51 may be referred to asthe a priori probability function. Further, while examples hereindisclose initialization probability function 49 and smoothed probabilityfunction 51 as a box and Gaussian shape, respectively, it iscontemplated that a wide variety of probability of distribution curveshapes may be utilized in any of the steps disclosed herein.

After generating smoothed probability function 51, processing system 32may multiply the activation signal 53 by the initialization probabilityfunction 49 to generate a posteriori probability distribution 55. Aposterior probability distribution 55 is illustrated under the “Beat 1”column of FIG. 11c . After generating a posterior probabilitydistribution 55, the greatest peak 43 of a posterior probabilitydistribution 55 is selected as the true activation time for beat 1 ofthe cardiac cycle.

After selecting peak 43, processing system 32 may perform aregularization step. The regularization step may include multiplyingfixed window 45 by a posterior probability distribution 55. In someembodiments, the regularization step may reduce the effects of adjacentbeats, which may otherwise accumulate over subsequent steps of thestatistical algorithm.

Lastly, a posterior probability 55 is time shifted one cardiac cycle(the steps of generation having been disclosed above) and is used as theinitialization probability distribution 55 of the subsequent beat in thecardiac cycle. The subsequent beat is illustrated in FIGS. 11a-11c underthe “Beat 2” column. At this point, the statistical algorithm repeatsitself, starting with smoothing the initialization probabilitydistribution 55. As the process repeats itself, it selects trueactivation times for each beat. However, as stated above, the activationtimes chosen for a given beat are influenced by prior data andprobability distributions derived from previous beats. In FIG. 11c , forexample, activation time 47 has been influenced by prior datacorresponding to beat 1. Similarly, activation time 59 has beeninfluenced by prior data corresponding to both beat 1 and beat 2 (asbeat 2 has been influenced by beat 1). In both cases, activation times47 and 59 have been chosen as the greatest peak on the posteriordistributions for beats 2 & 3, respectively.

After activation times (and/or corresponding fiducial points) have beenidentified, it may be desirable to display one or more processedoutputs. For example, in some embodiments in may be desirable to compareand categorize the derived activation times of the collected signals. Asdescribed above, it may be desirable to display relative activationtimes in an activation map. An example activation map 99 is shown inFIG. 10. FIG. 10 displays activation times corresponding to thesixty-four electrodes 24 on structure 20. However, while the numericalvalues may be useful, in practice the data may utilize a color scheme,patterns, or the like to convey the information.

It should be understood that processing system 32 may selectivelyeliminate some of the collected signals before performing the techniquesand/or embodiments disclosed herein. For example, it may be beneficialto eliminate signals collected by electrodes that are not in electricalcontact, or in poor electrical contact, with excitable cellular tissueof the heart. Such signals may not provide useful information and canskew results of the above described techniques. Further, processingsystem 32 may eliminate collected signals that do not cross a thresholdpower level and/or may eliminate collected signals that display athreshold amount of noise.

Alternatively, instead of eliminating collected signals that are notproviding useful information, processing system 32 may insteadinterpolate the value of any signal which is not otherwise providingdesirable information. Processing system 32 may utilize the interpolateddata (e.g. signal data) to better calculate, determine or generateuseful processed data and/or smooth, refine, or present processed datain a more desirable manner.

In at least some of the embodiments described above the disclosedmethods assume analysis of sensed, collected, measured and transmittedelectrical cellular data occurring during a single heartbeat and/orcardiac pulse. However, it is contemplated that any of the disclosedmethods may be implemented across multiple beats or cardiac pacing timeintervals. Further, data collected over multiple heart beats may beanalyzed using statistical methodologies and applied to the disclosedmethods. For example, activation times may be collected over a series ofheart beats and/or pulses. A statistical distribution of the collectedactivation times may be calculated, analyzed and incorporated intodisclosed methods.

It should be understood that this disclosure is, in many respects, onlyillustrative. Changes may be made in details, particularly in matters ofshape, size, and arrangement of steps without exceeding the scope of theinvention. This may include, to the extent that it is appropriate, theuse of any of the features of one example embodiment being used in otherembodiments. The invention's scope is, of course, defined in thelanguage in which the appended claims are expressed.

What is claimed is:
 1. A method of using a system to map electricalactivity of a heart, the system comprising (1) a mapping probe having aplurality of electrodes disposed at a distal end of the mapping probe,(2) a processing system, wherein each electrode of the plurality ofelectrodes is electrically coupled to the processing system, and (3) adisplay device coupled to the processing system, the method comprising:sensing a plurality of signals with the plurality of electrodespositioned within the heart; determining, by the processing system, adominant frequency of the plurality of signals; generating, by theprocessing system, an alternate signal for each of the plurality ofsignals corresponding to the dominant frequency, wherein each of thealternate signals has a phase-shift corresponding to one of theplurality of signals; determining, by the processing system, anactivation time corresponding to each of the plurality of signals,wherein determining the activation time corresponding to each of theplurality of signals comprises, for a first signal of the plurality ofsignals and a corresponding first alternate signal: determining a firsttime, the first time comprising a time at which a characteristic of thealternate signal occurs; creating a window of time around the firsttime; determining a second time, the second time comprising a time atwhich a characteristic of the first signal occurs; determining that thesecond time occurs within the window of time; and selecting, in responseto determining that the second time occurs within the window of time,the second time as the activation time corresponding to the firstsignal; generating, based on the determined activation times, anactivation map; and displaying, by the processing system and on thedisplay device, the activation map.
 2. The method of claim 1, whereindetermining a dominant frequency comprises: processing each of theplurality of signals using a Fourier Transform; generating a compositesignal based on the processed plurality of signals; identifying thefrequency with the maximum power in the composite signal.
 3. The methodof claim 2, further comprising band-pass filtering each of the processedplurality of signals.
 4. The method of claim 3, wherein the band-passfiltering comprises passing data in the 3 to 7 Hz band for each of theprocessed plurality of signals.
 5. The method of claim 2, whereingenerating the composite signal based on the processed plurality ofsignals comprises: generating the composite signal with a value at eachfrequency that is one of a median value, a mean value, or a mode valueof the processed plurality of signals at each frequency.
 6. The methodof claim 5, wherein the phase-shift of the alternate signals are basedon the composite signal.
 7. The method of claim 6, wherein eachalternate signal is a sinusoid.
 8. The method of claim 7, wherein eachalternate signal is an analytic representation of a sinusoid.
 9. Themethod of claim 8, wherein the analytic representation is generated by aHilbert transform.
 10. The method of claim 8, wherein the analyticrepresentation is a sawtooth.
 11. The method of claim 7, furthercomprising determining a fiducial point on each alternate signal, andwherein the fiducial point on each alternate signal is one of thefollowing: a point with a maximum negative derivative; a point ofzero-crossing; and a point at phase π/2.
 12. The method of claim 11,further comprising determining an activation time for each of theplurality of signals based on the identified fiducial points, generatingan activation map based on the determined activation times for each ofthe plurality of signals, and displaying the activation map.
 13. Asystem for mapping the electrical activity of the heart, the systemcomprising: a catheter shaft; a plurality of electrodes coupled to thecatheter shaft, the plurality of electrodes configured to sense aplurality of cardiac signals; and a processor coupled to the cathetershaft, wherein the processor is configured to: receive the plurality ofsignals sensed by the plurality of electrodes; determine a dominantfrequency of the plurality of signals; generate an alternate signal foreach of the plurality of signals corresponding to the dominantfrequency, wherein each of the alternate signals has a phase-shiftcorresponding to one of the plurality of signals; determine anactivation time corresponding to each of the plurality of signals,wherein to determine the activation time corresponding to each of theplurality of signals comprises, for a first signal of the plurality ofsignals and a corresponding first alternate signal: determine a firsttime comprising a time at which a characteristic of the alternate signaloccurs; create a window of time around the first time; determine asecond time comprising a time at which a characteristic of the firstsignal occurs; determine that the second time occurs within the windowof time; and select the second time as the activation time correspondingto the first signal in response to determining that the second timeoccurs within the window of time; generate an activation map based onthe determined activation times; and displaying the activation map. 14.The system of claim 13, wherein to determine a dominant frequency of theplurality of signals, the processor is further configured to: transformeach of the plurality of signals into the frequency domain; generate acomposite signal from each of the transformed plurality of signals; andidentify the frequency that has the maximum power in the compositesignal.
 15. The system of claim 13, wherein each alternate signal is ananalytic representation of a sinusoid.
 16. The system of claim 15,wherein the analytic representation is a sawtooth.